BAYESIAN-ESTIMATION OF NORMAL OGIVE ITEM RESPONSE CURVES USING GIBBS SAMPLING
BAYESIAN-ESTIMATION OF NORMAL OGIVE ITEM RESPONSE CURVES USING GIBBS SAMPLING
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DOI：
10.2307/1165149
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发表时间：
1992-09-01
期刊：
影响因子：
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通讯作者：
ALBERT, JH
中科院分区：
文献类型：
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作者：
ALBERT, JH
考虑从二参数正态尖顶模型估计项目参数的问题。吉布斯采样（Gelfand & Smith，1990）用于模拟能力和项目参数的联合后验分布的抽取。该方法给出任何感兴趣参数的边际后验密度估计；这些密度估计可用于判断基于最大似然估计的正态近似的准确性。使用数学分班考试的数据来说明这种模拟技术。
The problem of estimating item parameters from a two-parameter normal ogive model is considered. Gibbs sampling (Gelfand & Smith, 1990) is used to simulate draws from the joint posterior distribution of the ability and item parameters. This method gives marginal posterior density estimates for any parameter of interest; these density estimates can be used to judge the accuracy of normal approximations based on maximum likelihood estimates. This simulation technique is illustrated using data from a mathematics placement exam.